Multi-objective optimization for resin transfer molding process

A multi-objective optimization (MOO) approach for multi-point injection of resin-transfer molding (RTM) is proposed to investigate the trade-off relationship between productivity and quality for composite structures. With this approach, the optimum gate positions for their molding properties are evaluated using finite-element analysis (FEA) with a multiple-objective genetic algorithm (MOGA), and the trade-offs are visualized with the combination of a self-organizing map (SOM) and a scatter plot matrix (SPM). We applied this approach to RTM for flat-plate and rib models. For the flat-plate model, we found a negative correlation between fill time and weld line contents, and between fill time and dry spot contents. These results imply difficulty for simultaneous reduction of cycle time and void contents. For the rib model, some tendencies agree with those of the flat-plate model, and others do not. This difference comes from complexity of structure. We also found Pareto solutions that satisfy both productivity and quality for the flat-plate and rib models (i.e., gate positions such as a combination of diagonal and quadrangle positions for the flat-plate model, and aggregation of gate positions at a beam part for the rib model). Furthermore, we conducted simple experiments for the flat-plate model to validate the simulation result. The trends acquired from MOO qualitatively agree with the experiments.